Abstract #4143

One-Class Classifiers detect a specific endophenotype in young children with Autism Spectrum Disorders

Alessandra Retico¹, Ilaria Gori^1,2, Alessia Giuliano^1,3, Piernicola Oliva^1,2, Michela Tosetti⁴, Filippo Muratori^3,4, and Sara Calderoni⁴

¹National Institute of Nuclear Physics, Pisa, Italy, ²University of Sassari, Sassari, Italy, ³University of Pisa, Pisa, Italy, ⁴IRCCS Stella Maris Foundation, Pisa, Italy

Binary classifiers are widely used to analyze brain MRI features and to identify useful biomarkers of pathology. Strong challenges arise when dealing with extremely heterogeneous conditions such as Autism Spectrum Disorders (ASD). We propose the use of the One-Class Classifier (OCC) method that, in contrast to two-class classification, is based on the description of the positive class only. A test of similarity of new cases to the positive examples is then performed, and they are eventually considered as outliers. The application of OCC to Freesurfer-based brain MRI features identified a specific endophenotype in young children with ASD.

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